Abstract
This paper presents a Learning Analytics approach for understanding the learning behavior of students while interacting with Technology Enhanced Learning tools. In this work we show that it is possible to gain insight into the learning processes of students from their interaction data. We base our study on data collected through six laboratory sessions where first-year students of Computer Engineering at the University of Genoa were using a digital electronics simulator. We exploit Process Mining methods to investigate and compare the learning processes of students. For this purpose, we measure the understandability of their process models through a complexity metric. Then we compare the various clusters of students based on their academic achievements. The results show that the measured complexity has positive correlation with the final grades of students and negative correlation with the difficulty of the laboratory sessions. Consequently, complexity of process models can be used as an indicator of variations of student learning paths.
| Language | English |
|---|---|
| Title of host publication | Design for Teaching and Learning in a Networked World : 10th European Conference on Technology Enhanced Learning, EC-TEL 2015, Toledo, Spain, September 15–18, 2015 : Proceedings |
| Editors | G. Conole, T. Klobucar, C. Rensing, J. Konert, E. Lavoue |
| Place of Publication | Cham |
| Publisher | Springer |
| Pages | 352-366 |
| Number of pages | 15 |
| ISBN (Electronic) | 978-3-319-24258-3 |
| ISBN (Print) | 9783319242576 |
| DOIs | |
| State | Published - 2015 |
| Event | 10th European Conference on Technology Enhanced Learning (EC-TEL 2015), September 15-18, 2015, Toledo, Spain - Toledo, Spain Duration: 15 Sep 2015 → 18 Sep 2015 http://ectel2015.httc.de/index.php?id=704 |
Publication series
| Name | LNCS |
|---|---|
| Publisher | Springer |
| Volume | 9307 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 10th European Conference on Technology Enhanced Learning (EC-TEL 2015), September 15-18, 2015, Toledo, Spain |
|---|---|
| Abbreviated title | EC-TEL 2015 |
| Country | Spain |
| City | Toledo |
| Period | 15/09/15 → 18/09/15 |
| Other | "Design for Teaching and Learning in a Networked World" |
| Internet address |
Fingerprint
Keywords
- Complexity
- Educational data mining
- Educational simulator
- Interaction data
- Learning analytics
- Process mining
- Technology Enhanced Learning
Cite this
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A learning analytics approach to correlate the academic achievements of students with interaction data from an educational simulator. / Vahdat, M.; Oneto, L.; Anguita, D.; Funk, M.; Rauterberg, M.
Design for Teaching and Learning in a Networked World : 10th European Conference on Technology Enhanced Learning, EC-TEL 2015, Toledo, Spain, September 15–18, 2015 : Proceedings. ed. / G. Conole; T. Klobucar; C. Rensing; J. Konert; E. Lavoue. Cham : Springer, 2015. p. 352-366 (LNCS; Vol. 9307).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - A learning analytics approach to correlate the academic achievements of students with interaction data from an educational simulator
AU - Vahdat,M.
AU - Oneto,L.
AU - Anguita,D.
AU - Funk,M.
AU - Rauterberg,M.
PY - 2015
Y1 - 2015
N2 - This paper presents a Learning Analytics approach for understanding the learning behavior of students while interacting with Technology Enhanced Learning tools. In this work we show that it is possible to gain insight into the learning processes of students from their interaction data. We base our study on data collected through six laboratory sessions where first-year students of Computer Engineering at the University of Genoa were using a digital electronics simulator. We exploit Process Mining methods to investigate and compare the learning processes of students. For this purpose, we measure the understandability of their process models through a complexity metric. Then we compare the various clusters of students based on their academic achievements. The results show that the measured complexity has positive correlation with the final grades of students and negative correlation with the difficulty of the laboratory sessions. Consequently, complexity of process models can be used as an indicator of variations of student learning paths.
AB - This paper presents a Learning Analytics approach for understanding the learning behavior of students while interacting with Technology Enhanced Learning tools. In this work we show that it is possible to gain insight into the learning processes of students from their interaction data. We base our study on data collected through six laboratory sessions where first-year students of Computer Engineering at the University of Genoa were using a digital electronics simulator. We exploit Process Mining methods to investigate and compare the learning processes of students. For this purpose, we measure the understandability of their process models through a complexity metric. Then we compare the various clusters of students based on their academic achievements. The results show that the measured complexity has positive correlation with the final grades of students and negative correlation with the difficulty of the laboratory sessions. Consequently, complexity of process models can be used as an indicator of variations of student learning paths.
KW - Complexity
KW - Educational data mining
KW - Educational simulator
KW - Interaction data
KW - Learning analytics
KW - Process mining
KW - Technology Enhanced Learning
UR - http://www.scopus.com/inward/record.url?scp=84944704500&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-24258-3_26
DO - 10.1007/978-3-319-24258-3_26
M3 - Conference contribution
SN - 9783319242576
T3 - LNCS
SP - 352
EP - 366
BT - Design for Teaching and Learning in a Networked World : 10th European Conference on Technology Enhanced Learning, EC-TEL 2015, Toledo, Spain, September 15–18, 2015 : Proceedings
PB - Springer
CY - Cham
ER -